Digitally literate, habitually engaged: Unpacking sustainable urge to travel in coffee tourism

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Authors: Usep Suhud, Mamoon Allan, Wong Chee Hoo, Muaz Azinuddin, Sudhakar Madhavedi, Hasan Mukhibad, Doni Sugianto Sihotan
Cited by: 7
References: 1

Abstract

Despite the growing relevance of sustainable niche tourism, there is a lack of empirical studies on tourist consumer behavior in the context of coffee tourism—particularly regarding the factors that stimulate the urge to travel. The aim of the present study is to examine how digital literacy, habit, destination trust, and destination preference influence tourists’ urge to travel to coffee plantations. A conceptual framework was formulated to determine the ways in which habituated interaction between tourists and AI-based tourism infrastructure shapes tourists’ cognitions and affections to trust and preference, and these further drives travel enthusiasm. Data were gathered through an online survey on 225 tourists using convenient sampling. The measurement model was examined using Exploratory Factor Analysis (EFA), and the structural model and hypotheses were evaluated using Structural Equation Modelling (SEM) with AMOS version 29. The findings indicated that digital literacy had a significant and positive impact on the construction of habitual use of technology. Habit further emerged as an essential antecedent for destination trust and destination preference. Moreover, trust and preference were significant antecedents of tourists’ urge to travel. The model had superb fit indices (χ²/DF = 1.124, CFI = 0.995, RMSEA = 0.024), validating its theoretical construct and empirics. The findings provide deeper insights into consumer behavior, digital tourism consumption, and destination marketing practices, particularly, in response to the growing sustainability demands within the emerging context of coffee tourism.

Fields of Study & Subjects

Diverse Aspects of Tourism Research Digital Marketing and Social Media Wine Industry and Tourism

Publication details

Journal / source
International Journal of Data and Network Science
Publisher
Growing Science
Volume
10
Issue
2
Pages
925–938
Publication date
1 January 2026